Overview

Brought to you by YData

Dataset statistics

 Abalone TrainAbalone Test
Number of variables109
Number of observations9061560411
Missing cells00
Missing cells (%)0.0%0.0%
Duplicate rows00
Duplicate rows (%)0.0%0.0%
Total size in memory6.9 MiB4.1 MiB
Average record size in memory80.0 B72.0 B

Variable types

 Abalone TrainAbalone Test
Numeric98
Categorical11

Alerts

Abalone TrainAbalone Test
Diameter is highly overall correlated with Height and 6 other fieldsDiameter is highly overall correlated with Height and 5 other fieldsHigh correlation
Height is highly overall correlated with Diameter and 6 other fieldsHeight is highly overall correlated with Diameter and 5 other fieldsHigh correlation
Length is highly overall correlated with Diameter and 6 other fieldsLength is highly overall correlated with Diameter and 5 other fieldsHigh correlation
Rings is highly overall correlated with Diameter and 6 other fieldsAlert not present in this datasetHigh correlation
Shell weight is highly overall correlated with Diameter and 6 other fieldsShell weight is highly overall correlated with Diameter and 5 other fieldsHigh correlation
Whole weight is highly overall correlated with Diameter and 6 other fieldsWhole weight is highly overall correlated with Diameter and 5 other fieldsHigh correlation
Whole weight.1 is highly overall correlated with Diameter and 6 other fieldsWhole weight.1 is highly overall correlated with Diameter and 5 other fieldsHigh correlation
Whole weight.2 is highly overall correlated with Diameter and 6 other fieldsWhole weight.2 is highly overall correlated with Diameter and 5 other fieldsHigh correlation
id is uniformly distributed id is uniformly distributed Uniform
id has unique values id has unique values Unique

Reproduction

 Abalone TrainAbalone Test
Analysis started2025-05-18 17:22:59.0867742025-05-18 17:23:04.706494
Analysis finished2025-05-18 17:23:04.6998682025-05-18 17:23:09.113623
Duration5.61 seconds4.41 seconds
Software versionydata-profiling vv4.16.1ydata-profiling vv4.16.1
Download configurationconfig.jsonconfig.json

Variables

id
Real number (ℝ)

 Abalone TrainAbalone Test
Distinct9061560411
Distinct (%)100.0%100.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean45307120820
 Abalone TrainAbalone Test
Minimum090615
Maximum90614151025
Zeros10
Zeros (%)< 0.1%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size708.1 KiB472.1 KiB
2025-05-18T14:23:10.247050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Abalone TrainAbalone Test
Minimum090615
5-th percentile4530.793635.5
Q122653.5105717.5
median45307120820
Q367960.5135922.5
95-th percentile86083.3148004.5
Maximum90614151025
Range9061460410
Interquartile range (IQR)4530730205

Descriptive statistics

 Abalone TrainAbalone Test
Standard deviation26158.44217439.298
Coefficient of variation (CV)0.577359830.14434115
Kurtosis-1.2-1.2
Mean45307120820
Median Absolute Deviation (MAD)2265415103
Skewness00
Sum4.1054938 × 1097.298857 × 109
Variance6.8426407 × 1083.0412911 × 108
MonotonicityStrictly increasingStrictly increasing
2025-05-18T14:23:10.360554image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90614 1
 
< 0.1%
0 1
 
< 0.1%
1 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
90598 1
 
< 0.1%
90597 1
 
< 0.1%
90596 1
 
< 0.1%
Other values (90605) 90605
> 99.9%
ValueCountFrequency (%)
151025 1
 
< 0.1%
90615 1
 
< 0.1%
90616 1
 
< 0.1%
90617 1
 
< 0.1%
90618 1
 
< 0.1%
90619 1
 
< 0.1%
90620 1
 
< 0.1%
90621 1
 
< 0.1%
90622 1
 
< 0.1%
90623 1
 
< 0.1%
Other values (60401) 60401
> 99.9%
ValueCountFrequency (%)
0 1
< 0.1%
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
ValueCountFrequency (%)
90615 1
< 0.1%
90616 1
< 0.1%
90617 1
< 0.1%
90618 1
< 0.1%
90619 1
< 0.1%
90620 1
< 0.1%
90621 1
< 0.1%
90622 1
< 0.1%
90623 1
< 0.1%
90624 1
< 0.1%
ValueCountFrequency (%)
90615 1
< 0.1%
90616 1
< 0.1%
90617 1
< 0.1%
90618 1
< 0.1%
90619 1
< 0.1%
90620 1
< 0.1%
90621 1
< 0.1%
90622 1
< 0.1%
90623 1
< 0.1%
90624 1
< 0.1%
ValueCountFrequency (%)
0 1
< 0.1%
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%

Sex
Categorical

 Abalone TrainAbalone Test
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size708.1 KiB472.1 KiB
I
33093 
M
31027 
F
26495 
I
22241 
M
20783 
F
17387 

Length

 Abalone TrainAbalone Test
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 Abalone TrainAbalone Test
Total characters9061560411
Distinct characters33
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Abalone TrainAbalone Test
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Abalone TrainAbalone Test
1st rowFM
2nd rowFM
3rd rowIM
4th rowMM
5th rowII

Common Values

ValueCountFrequency (%)
I 33093
36.5%
M 31027
34.2%
F 26495
29.2%
ValueCountFrequency (%)
I 22241
36.8%
M 20783
34.4%
F 17387
28.8%

Length

2025-05-18T14:23:10.438545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Abalone Train

2025-05-18T14:23:10.476941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:10.508595image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
i 33093
36.5%
m 31027
34.2%
f 26495
29.2%
ValueCountFrequency (%)
i 22241
36.8%
m 20783
34.4%
f 17387
28.8%

Most occurring characters

ValueCountFrequency (%)
I 33093
36.5%
M 31027
34.2%
F 26495
29.2%
ValueCountFrequency (%)
I 22241
36.8%
M 20783
34.4%
F 17387
28.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 90615
100.0%
ValueCountFrequency (%)
Uppercase Letter 60411
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 33093
36.5%
M 31027
34.2%
F 26495
29.2%
ValueCountFrequency (%)
I 22241
36.8%
M 20783
34.4%
F 17387
28.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 90615
100.0%
ValueCountFrequency (%)
Latin 60411
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 33093
36.5%
M 31027
34.2%
F 26495
29.2%
ValueCountFrequency (%)
I 22241
36.8%
M 20783
34.4%
F 17387
28.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90615
100.0%
ValueCountFrequency (%)
ASCII 60411
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
I 33093
36.5%
M 31027
34.2%
F 26495
29.2%
ValueCountFrequency (%)
I 22241
36.8%
M 20783
34.4%
F 17387
28.8%

Length
Real number (ℝ)

 Abalone TrainAbalone Test
Distinct157148
Distinct (%)0.2%0.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.517098420.51742818
 Abalone TrainAbalone Test
Minimum0.0750.075
Maximum0.8150.8
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size708.1 KiB472.1 KiB
2025-05-18T14:23:10.585915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Abalone TrainAbalone Test
Minimum0.0750.075
5-th percentile0.280.28
Q10.4450.45
median0.5450.545
Q30.60.6
95-th percentile0.680.675
Maximum0.8150.8
Range0.740.725
Interquartile range (IQR)0.1550.15

Descriptive statistics

 Abalone TrainAbalone Test
Standard deviation0.118216710.1176087
Coefficient of variation (CV)0.228615490.22729474
Kurtosis0.13336380.14178863
Mean0.517098420.51742818
Median Absolute Deviation (MAD)0.070.07
Skewness-0.73201519-0.73456488
Sum46856.87431258.354
Variance0.013975190.013831807
MonotonicityNot monotonicNot monotonic
2025-05-18T14:23:10.697657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.575 3267
 
3.6%
0.58 2670
 
2.9%
0.57 2167
 
2.4%
0.55 2122
 
2.3%
0.595 1992
 
2.2%
0.525 1985
 
2.2%
0.6 1961
 
2.2%
0.585 1911
 
2.1%
0.53 1908
 
2.1%
0.565 1906
 
2.1%
Other values (147) 68726
75.8%
ValueCountFrequency (%)
0.575 2094
 
3.5%
0.58 1706
 
2.8%
0.57 1400
 
2.3%
0.6 1380
 
2.3%
0.55 1346
 
2.2%
0.525 1320
 
2.2%
0.595 1315
 
2.2%
0.585 1301
 
2.2%
0.53 1293
 
2.1%
0.565 1292
 
2.1%
Other values (138) 45964
76.1%
ValueCountFrequency (%)
0.075 4
 
< 0.1%
0.09 3
 
< 0.1%
0.1 2
 
< 0.1%
0.105 1
 
< 0.1%
0.11 11
< 0.1%
0.115 1
 
< 0.1%
0.12 2
 
< 0.1%
0.125 2
 
< 0.1%
0.13 24
< 0.1%
0.135 16
< 0.1%
ValueCountFrequency (%)
0.075 3
 
< 0.1%
0.09 1
 
< 0.1%
0.095 1
 
< 0.1%
0.1 3
 
< 0.1%
0.11 4
 
< 0.1%
0.125 4
 
< 0.1%
0.13 19
< 0.1%
0.135 8
 
< 0.1%
0.14 16
< 0.1%
0.15 21
< 0.1%
ValueCountFrequency (%)
0.075 3
 
< 0.1%
0.09 1
 
< 0.1%
0.095 1
 
< 0.1%
0.1 3
 
< 0.1%
0.11 4
 
< 0.1%
0.125 4
 
< 0.1%
0.13 19
< 0.1%
0.135 8
 
< 0.1%
0.14 16
< 0.1%
0.15 21
< 0.1%
ValueCountFrequency (%)
0.075 4
 
< 0.1%
0.09 3
 
< 0.1%
0.1 2
 
< 0.1%
0.105 1
 
< 0.1%
0.11 11
< 0.1%
0.115 1
 
< 0.1%
0.12 2
 
< 0.1%
0.125 2
 
< 0.1%
0.13 24
< 0.1%
0.135 16
< 0.1%

Diameter
Real number (ℝ)

 Abalone TrainAbalone Test
Distinct126130
Distinct (%)0.1%0.2%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.401679160.40196134
 Abalone TrainAbalone Test
Minimum0.0550.055
Maximum0.650.65
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size708.1 KiB472.1 KiB
2025-05-18T14:23:10.807169image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Abalone TrainAbalone Test
Minimum0.0550.055
5-th percentile0.210.21
Q10.3450.345
median0.4250.425
Q30.470.47
95-th percentile0.5350.535
Maximum0.650.65
Range0.5950.595
Interquartile range (IQR)0.1250.125

Descriptive statistics

 Abalone TrainAbalone Test
Standard deviation0.0980263190.097469695
Coefficient of variation (CV)0.244041340.24248525
Kurtosis0.000646264080.0040647768
Mean0.401679160.40196134
Median Absolute Deviation (MAD)0.060.055
Skewness-0.69523597-0.69631151
Sum36398.15724282.887
Variance0.00960915930.0095003414
MonotonicityNot monotonicNot monotonic
2025-05-18T14:23:10.914929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.45 4182
 
4.6%
0.475 3307
 
3.6%
0.455 2715
 
3.0%
0.4 2667
 
2.9%
0.47 2441
 
2.7%
0.465 2272
 
2.5%
0.46 2259
 
2.5%
0.425 2227
 
2.5%
0.44 2182
 
2.4%
0.435 2131
 
2.4%
Other values (116) 64232
70.9%
ValueCountFrequency (%)
0.45 2682
 
4.4%
0.475 2206
 
3.7%
0.455 1779
 
2.9%
0.4 1715
 
2.8%
0.47 1668
 
2.8%
0.465 1537
 
2.5%
0.46 1535
 
2.5%
0.44 1507
 
2.5%
0.425 1492
 
2.5%
0.435 1396
 
2.3%
Other values (120) 42894
71.0%
ValueCountFrequency (%)
0.055 1
 
< 0.1%
0.06 1
 
< 0.1%
0.065 1
 
< 0.1%
0.075 1
 
< 0.1%
0.085 2
 
< 0.1%
0.09 12
 
< 0.1%
0.095 4
 
< 0.1%
0.1 20
 
< 0.1%
0.103 1
 
< 0.1%
0.105 73
0.1%
ValueCountFrequency (%)
0.055 3
 
< 0.1%
0.07 1
 
< 0.1%
0.075 1
 
< 0.1%
0.08 2
 
< 0.1%
0.085 1
 
< 0.1%
0.09 7
 
< 0.1%
0.095 3
 
< 0.1%
0.1 18
 
< 0.1%
0.105 51
0.1%
0.11 51
0.1%
ValueCountFrequency (%)
0.055 3
 
< 0.1%
0.07 1
 
< 0.1%
0.075 1
 
< 0.1%
0.08 2
 
< 0.1%
0.085 1
 
< 0.1%
0.09 7
 
< 0.1%
0.095 3
 
< 0.1%
0.1 18
 
< 0.1%
0.105 51
0.1%
0.11 51
0.1%
ValueCountFrequency (%)
0.055 1
 
< 0.1%
0.06 1
 
< 0.1%
0.065 1
 
< 0.1%
0.075 1
 
< 0.1%
0.085 2
 
< 0.1%
0.09 12
 
< 0.1%
0.095 4
 
< 0.1%
0.1 20
 
< 0.1%
0.103 1
 
< 0.1%
0.105 73
0.1%

Height
Real number (ℝ)

 Abalone TrainAbalone Test
Distinct9085
Distinct (%)0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.135464060.13575108
 Abalone TrainAbalone Test
Minimum00
Maximum1.131.095
Zeros62
Zeros (%)< 0.1%< 0.1%
Negative00
Negative (%)0.0%0.0%
Memory size708.1 KiB472.1 KiB
2025-05-18T14:23:11.024750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Abalone TrainAbalone Test
Minimum00
5-th percentile0.070.07
Q10.110.11
median0.140.14
Q30.160.16
95-th percentile0.1950.195
Maximum1.131.095
Range1.131.095
Interquartile range (IQR)0.050.05

Descriptive statistics

 Abalone TrainAbalone Test
Standard deviation0.0380075620.038174758
Coefficient of variation (CV)0.280573040.28121145
Kurtosis13.45405117.693333
Mean0.135464060.13575108
Median Absolute Deviation (MAD)0.0250.025
Skewness0.309975060.55450613
Sum12275.0758200.8585
Variance0.00144457480.0014573121
MonotonicityNot monotonicNot monotonic
2025-05-18T14:23:11.130338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.15 5742
 
6.3%
0.14 5415
 
6.0%
0.155 5230
 
5.8%
0.145 5048
 
5.6%
0.135 4980
 
5.5%
0.125 4478
 
4.9%
0.175 4174
 
4.6%
0.16 3946
 
4.4%
0.165 3772
 
4.2%
0.13 3603
 
4.0%
Other values (80) 44227
48.8%
ValueCountFrequency (%)
0.15 3893
 
6.4%
0.14 3625
 
6.0%
0.155 3433
 
5.7%
0.135 3322
 
5.5%
0.145 3291
 
5.4%
0.125 3005
 
5.0%
0.16 2676
 
4.4%
0.175 2636
 
4.4%
0.165 2525
 
4.2%
0.13 2462
 
4.1%
Other values (75) 29543
48.9%
ValueCountFrequency (%)
0 6
 
< 0.1%
0.004 1
 
< 0.1%
0.005 3
 
< 0.1%
0.009 1
 
< 0.1%
0.01 4
 
< 0.1%
0.015 16
 
< 0.1%
0.019 1
 
< 0.1%
0.02 29
 
< 0.1%
0.025 100
0.1%
0.03 129
0.1%
ValueCountFrequency (%)
0 2
 
< 0.1%
0.005 2
 
< 0.1%
0.01 3
 
< 0.1%
0.0105 1
 
< 0.1%
0.015 6
 
< 0.1%
0.02 18
 
< 0.1%
0.025 62
 
0.1%
0.03 83
 
0.1%
0.035 113
0.2%
0.04 234
0.4%
ValueCountFrequency (%)
0 2
 
< 0.1%
0.005 2
 
< 0.1%
0.01 3
 
< 0.1%
0.0105 1
 
< 0.1%
0.015 6
 
< 0.1%
0.02 18
 
< 0.1%
0.025 62
 
0.1%
0.03 83
 
0.1%
0.035 113
0.1%
0.04 234
0.3%
ValueCountFrequency (%)
0 6
 
< 0.1%
0.004 1
 
< 0.1%
0.005 3
 
< 0.1%
0.009 1
 
< 0.1%
0.01 4
 
< 0.1%
0.015 16
 
< 0.1%
0.019 1
 
< 0.1%
0.02 29
 
< 0.1%
0.025 100
0.2%
0.03 129
0.2%

Whole weight
Real number (ℝ)

 Abalone TrainAbalone Test
Distinct31753037
Distinct (%)3.5%5.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.789034950.7900623
 Abalone TrainAbalone Test
Minimum0.0020.002
Maximum2.82552.8255
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size708.1 KiB472.1 KiB
2025-05-18T14:23:11.233073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Abalone TrainAbalone Test
Minimum0.0020.002
5-th percentile0.10750.1075
Q10.4190.4195
median0.79950.8015
Q31.06751.07
95-th percentile1.61851.6185
Maximum2.82552.8255
Range2.82352.8235
Interquartile range (IQR)0.64850.6505

Descriptive statistics

 Abalone TrainAbalone Test
Standard deviation0.45767070.45759058
Coefficient of variation (CV)0.580038560.5791829
Kurtosis-0.18513558-0.16542642
Mean0.789034950.7900623
Median Absolute Deviation (MAD)0.3220.322
Skewness0.429316260.43566352
Sum71498.40247728.454
Variance0.209462470.20938914
MonotonicityNot monotonicNot monotonic
2025-05-18T14:23:11.337700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5805 485
 
0.5%
0.7665 477
 
0.5%
0.974 361
 
0.4%
0.2225 347
 
0.4%
0.8295 325
 
0.4%
0.874 318
 
0.4%
0.6355 318
 
0.4%
1.4385 310
 
0.3%
0.879 306
 
0.3%
1.1345 301
 
0.3%
Other values (3165) 87067
96.1%
ValueCountFrequency (%)
0.5805 329
 
0.5%
0.7665 313
 
0.5%
0.8295 256
 
0.4%
0.974 254
 
0.4%
1.0265 225
 
0.4%
0.6355 221
 
0.4%
0.874 216
 
0.4%
0.2225 205
 
0.3%
0.9685 205
 
0.3%
0.873 202
 
0.3%
Other values (3027) 57985
96.0%
ValueCountFrequency (%)
0.002 2
 
< 0.1%
0.005 2
 
< 0.1%
0.0055 2
 
< 0.1%
0.0065 1
 
< 0.1%
0.008 6
 
< 0.1%
0.0095 1
 
< 0.1%
0.0105 34
< 0.1%
0.011 4
 
< 0.1%
0.0115 2
 
< 0.1%
0.012 2
 
< 0.1%
ValueCountFrequency (%)
0.002 2
 
< 0.1%
0.004 1
 
< 0.1%
0.0045 1
 
< 0.1%
0.0075 1
 
< 0.1%
0.008 9
< 0.1%
0.0095 2
 
< 0.1%
0.0105 17
< 0.1%
0.0115 2
 
< 0.1%
0.012 1
 
< 0.1%
0.0125 4
 
< 0.1%
ValueCountFrequency (%)
0.002 2
 
< 0.1%
0.004 1
 
< 0.1%
0.0045 1
 
< 0.1%
0.0075 1
 
< 0.1%
0.008 9
< 0.1%
0.0095 2
 
< 0.1%
0.0105 17
< 0.1%
0.0115 2
 
< 0.1%
0.012 1
 
< 0.1%
0.0125 4
 
< 0.1%
ValueCountFrequency (%)
0.002 2
 
< 0.1%
0.005 2
 
< 0.1%
0.0055 2
 
< 0.1%
0.0065 1
 
< 0.1%
0.008 6
 
< 0.1%
0.0095 1
 
< 0.1%
0.0105 34
0.1%
0.011 4
 
< 0.1%
0.0115 2
 
< 0.1%
0.012 2
 
< 0.1%

Whole weight.1
Real number (ℝ)

 Abalone TrainAbalone Test
Distinct17991747
Distinct (%)2.0%2.9%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.340778110.34122687
 Abalone TrainAbalone Test
Minimum0.0010.001
Maximum1.4881.488
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size708.1 KiB472.1 KiB
2025-05-18T14:23:11.444011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Abalone TrainAbalone Test
Minimum0.0010.001
5-th percentile0.0430.044
Q10.17750.1785
median0.330.329
Q30.4630.4645
95-th percentile0.71050.711
Maximum1.4881.488
Range1.4871.487
Interquartile range (IQR)0.28550.286

Descriptive statistics

 Abalone TrainAbalone Test
Standard deviation0.204428480.20422071
Coefficient of variation (CV)0.599887360.59848952
Kurtosis0.284011940.29017201
Mean0.340778110.34122687
Median Absolute Deviation (MAD)0.14350.1435
Skewness0.591973290.59320576
Sum30879.60820613.856
Variance0.0417910030.041706097
MonotonicityNot monotonicNot monotonic
2025-05-18T14:23:11.707113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.096 403
 
0.4%
0.3485 390
 
0.4%
0.2945 366
 
0.4%
0.3155 365
 
0.4%
0.4935 364
 
0.4%
0.3285 358
 
0.4%
0.3345 345
 
0.4%
0.4035 345
 
0.4%
0.5265 344
 
0.4%
0.3695 343
 
0.4%
Other values (1789) 86992
96.0%
ValueCountFrequency (%)
0.3485 280
 
0.5%
0.5305 246
 
0.4%
0.4235 242
 
0.4%
0.3155 239
 
0.4%
0.3695 239
 
0.4%
0.3285 237
 
0.4%
0.096 237
 
0.4%
0.4935 234
 
0.4%
0.2945 230
 
0.4%
0.3935 218
 
0.4%
Other values (1737) 58009
96.0%
ValueCountFrequency (%)
0.001 2
 
< 0.1%
0.0015 1
 
< 0.1%
0.002 2
 
< 0.1%
0.0025 9
 
< 0.1%
0.003 2
 
< 0.1%
0.0035 9
 
< 0.1%
0.004 4
 
< 0.1%
0.0045 29
< 0.1%
0.005 44
< 0.1%
0.0055 31
< 0.1%
ValueCountFrequency (%)
0.001 2
 
< 0.1%
0.0015 1
 
< 0.1%
0.002 1
 
< 0.1%
0.0025 3
 
< 0.1%
0.003 2
 
< 0.1%
0.004 2
 
< 0.1%
0.0045 15
< 0.1%
0.005 31
0.1%
0.0051 1
 
< 0.1%
0.0055 32
0.1%
ValueCountFrequency (%)
0.001 2
 
< 0.1%
0.0015 1
 
< 0.1%
0.002 1
 
< 0.1%
0.0025 3
 
< 0.1%
0.003 2
 
< 0.1%
0.004 2
 
< 0.1%
0.0045 15
< 0.1%
0.005 31
< 0.1%
0.0051 1
 
< 0.1%
0.0055 32
< 0.1%
ValueCountFrequency (%)
0.001 2
 
< 0.1%
0.0015 1
 
< 0.1%
0.002 2
 
< 0.1%
0.0025 9
 
< 0.1%
0.003 2
 
< 0.1%
0.0035 9
 
< 0.1%
0.004 4
 
< 0.1%
0.0045 29
< 0.1%
0.005 44
0.1%
0.0055 31
0.1%

Whole weight.2
Real number (ℝ)

 Abalone TrainAbalone Test
Distinct979960
Distinct (%)1.1%1.6%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.169421840.16941934
 Abalone TrainAbalone Test
Minimum0.00050.0005
Maximum0.760.6415
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size708.1 KiB472.1 KiB
2025-05-18T14:23:11.815516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Abalone TrainAbalone Test
Minimum0.00050.0005
5-th percentile0.0230.0235
Q10.08650.0865
median0.1660.166
Q30.23250.2325
95-th percentile0.35550.3555
Maximum0.760.6415
Range0.75950.641
Interquartile range (IQR)0.1460.146

Descriptive statistics

 Abalone TrainAbalone Test
Standard deviation0.100908890.10072047
Coefficient of variation (CV)0.595607310.59450393
Kurtosis-0.20372097-0.20488298
Mean0.169421840.16941934
Median Absolute Deviation (MAD)0.07350.073
Skewness0.476733340.47612882
Sum15352.1610234.792
Variance0.0101826040.010144612
MonotonicityNot monotonicNot monotonic
2025-05-18T14:23:11.924972image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1715 799
 
0.9%
0.1725 689
 
0.8%
0.2195 611
 
0.7%
0.1625 525
 
0.6%
0.2145 501
 
0.6%
0.1815 500
 
0.6%
0.0265 494
 
0.5%
0.1825 480
 
0.5%
0.1405 474
 
0.5%
0.1905 470
 
0.5%
Other values (969) 85072
93.9%
ValueCountFrequency (%)
0.1715 540
 
0.9%
0.1725 445
 
0.7%
0.2195 417
 
0.7%
0.0265 375
 
0.6%
0.1625 365
 
0.6%
0.2145 349
 
0.6%
0.1815 324
 
0.5%
0.1405 321
 
0.5%
0.1825 318
 
0.5%
0.1905 303
 
0.5%
Other values (950) 56654
93.8%
ValueCountFrequency (%)
0.0005 17
 
< 0.1%
0.001 3
 
< 0.1%
0.0015 3
 
< 0.1%
0.002 7
 
< 0.1%
0.0025 53
 
0.1%
0.003 37
 
< 0.1%
0.0035 83
0.1%
0.004 5
 
< 0.1%
0.0045 106
0.1%
0.005 169
0.2%
ValueCountFrequency (%)
0.0005 14
 
< 0.1%
0.001 2
 
< 0.1%
0.0015 1
 
< 0.1%
0.002 4
 
< 0.1%
0.0025 43
0.1%
0.003 18
 
< 0.1%
0.0035 45
0.1%
0.004 6
 
< 0.1%
0.0045 68
0.1%
0.005 89
0.1%
ValueCountFrequency (%)
0.0005 14
 
< 0.1%
0.001 2
 
< 0.1%
0.0015 1
 
< 0.1%
0.002 4
 
< 0.1%
0.0025 43
< 0.1%
0.003 18
 
< 0.1%
0.0035 45
< 0.1%
0.004 6
 
< 0.1%
0.0045 68
0.1%
0.005 89
0.1%
ValueCountFrequency (%)
0.0005 17
 
< 0.1%
0.001 3
 
< 0.1%
0.0015 3
 
< 0.1%
0.002 7
 
< 0.1%
0.0025 53
 
0.1%
0.003 37
 
0.1%
0.0035 83
0.1%
0.004 5
 
< 0.1%
0.0045 106
0.2%
0.005 169
0.3%

Shell weight
Real number (ℝ)

 Abalone TrainAbalone Test
Distinct11291089
Distinct (%)1.2%1.8%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean0.225897840.22612471
 Abalone TrainAbalone Test
Minimum0.00150.0015
Maximum1.0051.004
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size708.1 KiB472.1 KiB
2025-05-18T14:23:12.030667image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Abalone TrainAbalone Test
Minimum0.00150.0015
5-th percentile0.0310.0325
Q10.120.12
median0.2250.225
Q30.3050.305
95-th percentile0.460.46
Maximum1.0051.004
Range1.00351.0025
Interquartile range (IQR)0.1850.185

Descriptive statistics

 Abalone TrainAbalone Test
Standard deviation0.130203340.12982647
Coefficient of variation (CV)0.57638150.5741366
Kurtosis0.0960489660.042671196
Mean0.225897840.22612471
Median Absolute Deviation (MAD)0.09050.0915
Skewness0.479092490.46852363
Sum20469.73313660.42
Variance0.0169529090.016854912
MonotonicityNot monotonicNot monotonic
2025-05-18T14:23:12.130939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.24 1628
 
1.8%
0.22 1269
 
1.4%
0.25 1259
 
1.4%
0.275 1211
 
1.3%
0.265 1200
 
1.3%
0.295 1131
 
1.2%
0.27 1130
 
1.2%
0.17 1094
 
1.2%
0.26 1049
 
1.2%
0.285 1008
 
1.1%
Other values (1119) 78636
86.8%
ValueCountFrequency (%)
0.24 1009
 
1.7%
0.22 880
 
1.5%
0.265 837
 
1.4%
0.25 829
 
1.4%
0.17 784
 
1.3%
0.26 762
 
1.3%
0.275 756
 
1.3%
0.27 726
 
1.2%
0.295 719
 
1.2%
0.28 677
 
1.1%
Other values (1079) 52432
86.8%
ValueCountFrequency (%)
0.0015 4
 
< 0.1%
0.0018 1
 
< 0.1%
0.002 1
 
< 0.1%
0.0025 8
 
< 0.1%
0.003 14
 
< 0.1%
0.0035 22
 
< 0.1%
0.004 20
 
< 0.1%
0.0045 4
 
< 0.1%
0.005 299
0.3%
0.0055 11
 
< 0.1%
ValueCountFrequency (%)
0.0015 6
 
< 0.1%
0.0025 4
 
< 0.1%
0.003 5
 
< 0.1%
0.0035 7
 
< 0.1%
0.004 20
 
< 0.1%
0.0045 3
 
< 0.1%
0.005 188
0.3%
0.0055 8
 
< 0.1%
0.006 16
 
< 0.1%
0.0065 13
 
< 0.1%
ValueCountFrequency (%)
0.0015 6
 
< 0.1%
0.0025 4
 
< 0.1%
0.003 5
 
< 0.1%
0.0035 7
 
< 0.1%
0.004 20
 
< 0.1%
0.0045 3
 
< 0.1%
0.005 188
0.2%
0.0055 8
 
< 0.1%
0.006 16
 
< 0.1%
0.0065 13
 
< 0.1%
ValueCountFrequency (%)
0.0015 4
 
< 0.1%
0.0018 1
 
< 0.1%
0.002 1
 
< 0.1%
0.0025 8
 
< 0.1%
0.003 14
 
< 0.1%
0.0035 22
 
< 0.1%
0.004 20
 
< 0.1%
0.0045 4
 
< 0.1%
0.005 299
0.5%
0.0055 11
 
< 0.1%

Rings
Real number (ℝ)

Distinct28
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.6967941
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.1 KiB
2025-05-18T14:23:12.199505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q18
median9
Q311
95-th percentile16
Maximum29
Range28
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.1762209
Coefficient of variation (CV)0.32755372
Kurtosis2.6129342
Mean9.6967941
Median Absolute Deviation (MAD)2
Skewness1.204273
Sum878675
Variance10.088379
MonotonicityNot monotonic
2025-05-18T14:23:12.254405image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
9 17465
19.3%
8 14499
16.0%
10 12464
13.8%
7 9008
9.9%
11 8407
9.3%
6 5411
 
6.0%
12 4719
 
5.2%
13 4074
 
4.5%
5 2862
 
3.2%
14 2507
 
2.8%
Other values (18) 9199
10.2%
ValueCountFrequency (%)
1 25
 
< 0.1%
2 29
 
< 0.1%
3 386
 
0.4%
4 1402
 
1.5%
5 2862
 
3.2%
6 5411
 
6.0%
7 9008
9.9%
8 14499
16.0%
9 17465
19.3%
10 12464
13.8%
ValueCountFrequency (%)
29 24
 
< 0.1%
27 41
 
< 0.1%
26 18
 
< 0.1%
25 22
 
< 0.1%
24 29
 
< 0.1%
23 180
 
0.2%
22 108
 
0.1%
21 255
 
0.3%
20 507
0.6%
19 639
0.7%

Interactions

Abalone Train

2025-05-18T14:23:03.812649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:22:59.595257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.115461image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:00.103458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.598326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:00.799668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.075243image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.290161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.532254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.770827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.963950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.258444image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.387442image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.768696image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.855795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.289813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.337375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.872972image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:22:59.647949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.173772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:00.161864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.659064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:00.854350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.134184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.341100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.589907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.823741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.017081image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.314037image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.445181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.824334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.920033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.342257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.396397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.936023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:22:59.706877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.235061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:00.370639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.719988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:00.911906image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.191988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.396666image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.648818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.879535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.071397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.372462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.502534image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.882353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.984359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.398781image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.456032image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.993850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:22:59.762286image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.297796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:00.431102image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.777675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:00.964157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.247640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.448759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.702277image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.932281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.123971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.429010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.558497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.938811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.041759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.451872image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.665014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:04.052604image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:22:59.817443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.360480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:00.490590image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.835504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.017653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.302862image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.500919image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.754577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.985861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.175375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.483694image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.611513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.994145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.100093image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.504579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.720435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:04.263245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:22:59.872563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.417984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:00.552140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.895265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.070645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.359864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.553592image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.805619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.037437image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.226774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.538941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.666106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.050911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.158544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.559327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.776788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:04.325225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:22:59.931969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.480093image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:00.615193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.956602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.127784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.418839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.609304image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.860057image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.094682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.281677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.597214image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.728076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.112293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.220417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.623564image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.835058image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:04.386194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:22:59.990055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:05.539138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:00.678624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.017246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.183196image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.476757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:01.664742image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:06.912232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.150568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.335708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:02.655859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:07.792440image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.175322image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.278489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:03.688791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:08.893061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

2025-05-18T14:23:04.444927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:23:00.047492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:23:00.738147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:23:01.235585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:23:01.717591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:23:02.205065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:23:02.711787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:23:03.231856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Abalone Train

2025-05-18T14:23:03.748535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test


Interaction plot not present for dataset

Correlations

Abalone Train

2025-05-18T14:23:12.302433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Test

2025-05-18T14:23:12.382613image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Abalone Train

DiameterHeightLengthRingsSexShell weightWhole weightWhole weight.1Whole weight.2id
Diameter1.0000.9210.9850.7200.4860.9620.9780.9610.9620.004
Height0.9211.0000.9160.7570.4340.9410.9360.9010.9240.005
Length0.9850.9161.0000.7080.4800.9560.9760.9640.9610.005
Rings0.7200.7570.7081.0000.4100.7870.7360.6620.7240.003
Sex0.4860.4340.4800.4101.0000.4960.4960.4700.4960.008
Shell weight0.9620.9410.9560.7870.4961.0000.9740.9340.9550.005
Whole weight0.9780.9360.9760.7360.4960.9741.0000.9770.9800.005
Whole weight.10.9610.9010.9640.6620.4700.9340.9771.0000.9590.003
Whole weight.20.9620.9240.9610.7240.4960.9550.9800.9591.0000.004
id0.0040.0050.0050.0030.0080.0050.0050.0030.0041.000

Abalone Test

DiameterHeightLengthSexShell weightWhole weightWhole weight.1Whole weight.2id
Diameter1.0000.9200.9850.4840.9610.9770.9610.9610.010
Height0.9201.0000.9150.4030.9410.9360.9010.9240.007
Length0.9850.9151.0000.4770.9550.9760.9640.9610.009
Sex0.4840.4030.4771.0000.4930.4930.4680.4950.000
Shell weight0.9610.9410.9550.4931.0000.9740.9340.9550.008
Whole weight0.9770.9360.9760.4930.9741.0000.9770.9800.009
Whole weight.10.9610.9010.9640.4680.9340.9771.0000.9600.009
Whole weight.20.9610.9240.9610.4950.9550.9800.9601.0000.008
id0.0100.0070.0090.0000.0080.0090.0090.0081.000

Missing values

Abalone Train

2025-05-18T14:23:04.526378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.

Abalone Test

2025-05-18T14:23:08.971998image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.

Abalone Train

2025-05-18T14:23:04.607172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Abalone Test

2025-05-18T14:23:09.038945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Abalone Train

idSexLengthDiameterHeightWhole weightWhole weight.1Whole weight.2Shell weightRings
00F0.5500.4300.1500.77150.32850.14650.240011
11F0.6300.4900.1451.13000.45800.27650.320011
22I0.1600.1100.0250.02100.00550.00300.00506
33M0.5950.4750.1500.91450.37550.20550.250010
44I0.5550.4250.1300.78200.36950.16000.19759
55F0.6100.4800.1701.20100.53350.31350.308510
66M0.4150.3250.1100.33150.16550.07150.13009
77F0.6100.4900.1501.11650.49550.29450.29509
88I0.2050.1500.0400.04600.01450.01050.01004
99I0.5650.4250.1250.65100.37950.14200.18008

Abalone Test

idSexLengthDiameterHeightWhole weightWhole weight.1Whole weight.2Shell weight
090615M0.6450.4750.1551.23800.61850.31250.3005
190616M0.5800.4600.1600.98300.47850.21950.2750
290617M0.5600.4200.1400.83950.35250.18450.2405
390618M0.5700.4900.1450.87400.35250.18650.2350
490619I0.4150.3250.1100.35800.15750.06700.1050
590620M0.5600.4250.1400.81050.35250.19150.2150
690621M0.6350.4900.1701.18350.46050.24450.3550
790622I0.3400.2500.0750.16750.07500.03300.0480
890623I0.4850.3700.1100.53600.25650.09800.1490
990624F0.6400.5000.1951.33800.64700.31750.3965

Abalone Train

idSexLengthDiameterHeightWhole weightWhole weight.1Whole weight.2Shell weightRings
9060590605M0.5600.4500.1550.90550.39250.17750.28009
9060690606M0.5750.4500.1651.09850.37650.21500.400014
9060790607F0.5550.4250.1550.87900.34100.20650.250010
9060890608I0.3500.2650.0750.17350.07600.05900.05256
9060990609F0.6500.5250.1851.70700.66050.35450.473514
9061090610M0.3350.2350.0750.15850.06850.03700.04506
9061190611M0.5550.4250.1500.87900.38650.18150.24009
9061290612I0.4350.3300.0950.32150.15100.07850.08156
9061390613I0.3450.2700.0750.20000.09800.04900.07006
9061490614I0.4250.3250.1000.34550.15250.07850.10508

Abalone Test

idSexLengthDiameterHeightWhole weightWhole weight.1Whole weight.2Shell weight
60401151016F0.5850.4550.1550.91250.31250.19350.3200
60402151017I0.4000.3150.0950.26450.11500.05300.0740
60403151018F0.6050.4750.1450.97400.43050.23000.3150
60404151019I0.5600.4300.1300.76500.30650.17400.2565
60405151020M0.5700.4350.1250.92650.36850.20150.2950
60406151021I0.3450.2600.0850.17750.07350.02650.0500
60407151022F0.5250.4100.1450.84450.38850.16700.2050
60408151023I0.5900.4400.1551.12200.39300.20000.2650
60409151024F0.6600.5250.1901.49350.58850.35750.4350
60410151025F0.4300.3400.1200.41500.15250.09100.0905

Duplicate rows

Abalone Train

idSexLengthDiameterHeightWhole weightWhole weight.1Whole weight.2Shell weightRings# duplicates
Dataset does not contain duplicate rows.

Abalone Test

idSexLengthDiameterHeightWhole weightWhole weight.1Whole weight.2Shell weight# duplicates
Dataset does not contain duplicate rows.